TY - GEN
T1 - Battery management and application for energy-efficient
AU - Wei, Tianshu
AU - Kim, Taeyoung
AU - Park, Sangyoung
AU - Zhu, Qi
AU - Tan, Sheldon X D
AU - Chang, Naehyuck
AU - Ula, Sadrul
AU - Maasoumy, Mehdi
PY - 2014
Y1 - 2014
N2 - As the building stock consumes 40% of the U.S. primary energy consumption, it is critically important to improve building energy effciency. This involves reducing the total energy consumption of buildings, reducing the peak energy demand, and leveraging renewable energy sources, etc. To achieve such goals, hybrid energy supply has becoming pop-ular, where multiple energy sources such as grid electricity, on-site fuel cell generators, solar, wind, and battery storage are scheduled together to improve energy effciency. In this work, we focus on the application and manage-ment of battery storage for energy-effcient buildings. We will rst introduce a system-level approach to co-schedule the usage of battery storage (in addition to grid electricity) with the control of building HVAC (heating, ventilation, and air conditioning) system, to reduce the total building energy cost, including the electricity consumption charge, the peak demand charge, and the battery cost. Then, in a separate formulation, we will introduce another system-level study to reduce the energy cost of EV charging and other xed building energy load through the usage of battery storage and solar PV. Finally, we will present an ARM processor based programmable embedded battery management sys-tem (BMS), which monitors battery status, controls charg-ing and discharging at the circuit level, and provides battery protection. The system also works with off-the-shelf battery management IC (Texas Instrument BMS sensor IC) from industry. Comparing to conventional BMS, this software module based BMS is a more suitable solution for energy-effcient buildings due to its high exibility, scalability, and reusability. We will introduce an industrial building testbed with bat-tery storage and solar PV at the University of California, Riverside, and present initial eld tests and simulation re-sults for above approaches.
AB - As the building stock consumes 40% of the U.S. primary energy consumption, it is critically important to improve building energy effciency. This involves reducing the total energy consumption of buildings, reducing the peak energy demand, and leveraging renewable energy sources, etc. To achieve such goals, hybrid energy supply has becoming pop-ular, where multiple energy sources such as grid electricity, on-site fuel cell generators, solar, wind, and battery storage are scheduled together to improve energy effciency. In this work, we focus on the application and manage-ment of battery storage for energy-effcient buildings. We will rst introduce a system-level approach to co-schedule the usage of battery storage (in addition to grid electricity) with the control of building HVAC (heating, ventilation, and air conditioning) system, to reduce the total building energy cost, including the electricity consumption charge, the peak demand charge, and the battery cost. Then, in a separate formulation, we will introduce another system-level study to reduce the energy cost of EV charging and other xed building energy load through the usage of battery storage and solar PV. Finally, we will present an ARM processor based programmable embedded battery management sys-tem (BMS), which monitors battery status, controls charg-ing and discharging at the circuit level, and provides battery protection. The system also works with off-the-shelf battery management IC (Texas Instrument BMS sensor IC) from industry. Comparing to conventional BMS, this software module based BMS is a more suitable solution for energy-effcient buildings due to its high exibility, scalability, and reusability. We will introduce an industrial building testbed with bat-tery storage and solar PV at the University of California, Riverside, and present initial eld tests and simulation re-sults for above approaches.
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U2 - 10.1145/2593069.2596670
DO - 10.1145/2593069.2596670
M3 - Conference contribution
AN - SCOPUS:84903180569
SN - 9781479930173
T3 - Proceedings - Design Automation Conference
BT - DAC 2014 - 51st Design Automation Conference, Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 51st Annual Design Automation Conference, DAC 2014
Y2 - 2 June 2014 through 5 June 2014
ER -